Datenschutzerklärung|Data Privacy
Impressum

06.08.2018
K. Forster

"ScootR: Scaling R Dataframes on Dataflow Systems" Paper Accepted at SoCC 2018

"ScootR: Scaling R Dataframes on Dataflow Systems", Andreas Kunft, Lukas Stadler, Daniele Bonetta, Cosmin Basca, Jens Meiners, Sebastian Breß, Tilmann Rabl, Juan Fumero and Volker Markl . 2018. Symposium of Cloud Computing (SoCC '18) conference.

Abstract
To cope with today's large scale of data, parallel dataflow engines such as Hadoop, and more recently Spark and Flink, have been proposed. They offer scalability and performance, but require data scientists to develop analysis pipelines in unfamiliar programming languages and abstractions. To overcome this hurdle, dataflow engines have introduced some forms of multi-language integrations, e.g., for Python and R. However, this results in data exchange between the dataflow engine and the integrated language runtime, which requires inter-process communication and causes high runtime overheads.

In this paper, we present ScootR, a novel approach to execute R in dataflow systems. ScootR tightly integrates the dataflow and R language runtime by using the Truffle framework and the Graal compiler. As a result, ScootR executes R scripts directly in the Flink data processing engine, without serialization and inter-process communication. Our experimental study reveals that ScootR outperforms state-of-the-art systems by up to an order of magnitude.

Link to paper preprint